Abstract: This research proposes an algorithm for the simulation
of time-periodic unsteady problems via the solution unsteady Euler
and Navier-Stokes equations. This algorithm which is called Time
Spectral method uses a Fourier representation in time and hence
solve for the periodic state directly without resolving transients
(which consume most of the resources in a time-accurate scheme).
Mathematical tools used here are discrete Fourier transformations. It
has shown tremendous potential for reducing the computational cost
compared to conventional time-accurate methods, by enforcing
periodicity and using Fourier representation in time, leading to
spectral accuracy. The accuracy and efficiency of this technique is
verified by Euler and Navier-Stokes calculations for pitching airfoils.
Because of flow turbulence nature, Baldwin-Lomax turbulence
model has been used at viscous flow analysis. The results presented
by the Time Spectral method are compared with experimental data. It
has shown tremendous potential for reducing the computational cost
compared to the conventional time-accurate methods, by enforcing
periodicity and using Fourier representation in time, leading to
spectral accuracy, because results verify the small number of time
intervals per pitching cycle required to capture the flow physics.
Abstract: In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.
Abstract: The main aim of this work is to establish the
capabilities of new green buildings to ascertain off-grid electricity
generation based on the integration of wind turbines in the
conceptual model of a rotating tower [2] in Dubai. An in depth
performance analysis of the WinWind 3.0MW [3] wind turbine is
performed. Data based on the Dubai Meteorological Services is
collected and analyzed in conjunction with the performance analysis
of this wind turbine. The mathematical model is compared with
Computational Fluid Dynamics (CFD) results based on a conceptual
rotating tower design model. The comparison results are further
validated and verified for accuracy by conducting experiments on a
scaled prototype of the tower design. The study concluded that
integrating wind turbines inside a rotating tower can generate enough
electricity to meet the required power consumption of the building,
which equates to a wind farm containing 9 horizontal axis wind
turbines located at an approximate area of 3,237,485 m2 [14].
Abstract: This paper presents a novel iris recognition system
using 1D log polar Gabor wavelet and Euler numbers. 1D log polar
Gabor wavelet is used to extract the textural features, and Euler
numbers are used to extract topological features of the iris. The
proposed decision strategy uses these features to authenticate an
individual-s identity while maintaining a low false rejection rate. The
algorithm was tested on CASIA iris image database and found to
perform better than existing approaches with an overall accuracy of
99.93%.
Abstract: Advances in clinical medical imaging have brought about the routine production of vast numbers of medical images that need to be analyzed. As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis. Computed Tomography (CT) is highly accurate for diagnosing liver tumors. This study aimed to evaluate the potential role of the wavelet and the neural network in the differential diagnosis of liver tumors in CT images. The tumors considered in this study are hepatocellular carcinoma, cholangio carcinoma, hemangeoma and hepatoadenoma. Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors. Results obtained were evaluated with the help of radiologists. The system differentiates the tumor with relatively high accuracy and is therefore clinically useful.
Abstract: In the last two decades radiofrequency ablation (RFA)
has been considered a promising medical procedure for the treatment
of primary and secondary malignancies. However, the needle-based
electrodes so far developed for this kind of treatment are not suitable
for the thermal ablation of tumors located in hollow organs like
esophagus, colon or bile duct. In this work a tubular electrode
solution is presented. Numerical and experimental analyses were
performed to characterize the volume of the lesion induced. Results
show that this kind of electrode is a feasible solution and numerical
simulation might provide a tool for planning RFA procedure with
some accuracy.
Abstract: In the recent works related with mixture discriminant
analysis (MDA), expectation and maximization (EM) algorithm is
used to estimate parameters of Gaussian mixtures. But, initial values
of EM algorithm affect the final parameters- estimates. Also, when
EM algorithm is applied two times, for the same data set, it can be
give different results for the estimate of parameters and this affect the
classification accuracy of MDA. Forthcoming this problem, we use
Self Organizing Mixture Network (SOMN) algorithm to estimate
parameters of Gaussians mixtures in MDA that SOMN is more robust
when random the initial values of the parameters are used [5]. We
show effectiveness of this method on popular simulated waveform
datasets and real glass data set.
Abstract: Shadow detection is still considered as one of the
potential challenges for intelligent automated video surveillance
systems. A pre requisite for reliable and accurate detection and
tracking is the correct shadow detection and classification. In such a
landscape of conditions, privacy issues add more and more
complexity and require reliable shadow detection.
In this work the intertwining between security, accuracy,
reliability and privacy is analyzed and, accordingly, a novel
architecture for Privacy Enhancing Video Surveillance (PEVS) is
introduced. Shadow detection and masking are dealt with through the
combination of two different approaches simultaneously. This results
in a unique privacy enhancement, without affecting security.
Subsequently, the methodology was employed successfully in a
large-scale wireless video surveillance system; privacy relevant
information was stored and encrypted on the unit, without
transferring it over an un-trusted network.
Abstract: The use of electronic sensors in the electronics
industry has become increasingly popular over the past few years,
and it has become a high competition product. The frequency
adjustment process is regarded as one of the most important process
in the electronic sensor manufacturing process. Due to inaccuracies
in the frequency adjustment process, up to 80% waste can be caused
due to rework processes; therefore, this study aims to provide a
preliminary understanding of the role of parameters used in the
frequency adjustment process, and also make suggestions in order to
further improve performance. Four parameters are considered in this
study: air pressure, dispensing time, vacuum force, and the distance
between the needle tip and the product. A full factorial design for
experiment 2k was considered to determine those parameters that
significantly affect the accuracy of the frequency adjustment process,
where a deviation in the frequency after adjustment and the target
frequency is expected to be 0 kHz. The experiment was conducted on
two levels, using two replications and with five center-points added.
In total, 37 experiments were carried out. The results reveal that air
pressure and dispensing time significantly affect the frequency
adjustment process. The mathematical relationship between these
two parameters was formulated, and the optimal parameters for air
pressure and dispensing time were found to be 0.45 MPa and 458 ms,
respectively. The optimal parameters were examined by carrying out
a confirmation experiment in which an average deviation of 0.082
kHz was achieved.
Abstract: This study comprehensively simulate the use of k-ε
model for predicting flow and heat transfer with measured flow field
data in a stationary duct with elucidates on the detailed physics
encountered in the fully developed flow region, and the sharp 180°
bend region. Among the major flow features predicted with accuracy
are flow transition at the entrance of the duct, the distribution of
mean and turbulent quantities in the developing, fully developed, and
sharp 180° bend, the development of secondary flows in the duct
cross-section and the sharp 180° bend, and heat transfer
augmentation. Turbulence intensities in the sharp 180° bend are
found to reach high values and local heat transfer comparisons show
that the heat transfer augmentation shifts towards the wall and along
the duct. Therefore, understanding of the unsteady heat transfer in
sharp 180° bends is important. The design and simulation are related
to concept of fluid mechanics, heat transfer and thermodynamics.
Simulation study has been conducted on the response of turbulent
flow in a rectangular duct in order to evaluate the heat transfer rate
along the small scale multiple rectangular duct
Abstract: Three-dimensional reconstruction of small objects has
been one of the most challenging problems over the last decade.
Computer graphics researchers and photography professionals have
been working on improving 3D reconstruction algorithms to fit the
high demands of various real life applications. Medical sciences,
animation industry, virtual reality, pattern recognition, tourism
industry, and reverse engineering are common fields where 3D
reconstruction of objects plays a vital role. Both lack of accuracy and
high computational cost are the major challenges facing successful
3D reconstruction. Fringe projection has emerged as a promising 3D
reconstruction direction that combines low computational cost to both
high precision and high resolution. It employs digital projection,
structured light systems and phase analysis on fringed pictures.
Research studies have shown that the system has acceptable
performance, and moreover it is insensitive to ambient light.
This paper presents an overview of fringe projection approaches. It
also presents an experimental study and implementation of a simple
fringe projection system. We tested our system using two objects
with different materials and levels of details. Experimental results
have shown that, while our system is simple, it produces acceptable
results.
Abstract: A good green building design project, designers should consider not only energy consumption, but also healthy and comfortable needs of inhabitants. In recent years, the Taiwan government paid attentions on both carbon reduction and indoor air quality issues, which be presented in the legislation of Building Codes and other regulations. Taiwan located in hot and humid climates, dampness in buildings leads to significant microbial pollution and building damage. This means that the high temperature and humidity present a serious indoor air quality issue. The interactions between vapor transfers and energy fluxes are essential for the whole building Heat Air and Moisture (HAM) response. However, a simulation tool with short calculation time, property accuracy and interface is needed for practical building design processes. In this research, we consider the vapor transfer phenomenon of building materials as well as temperature and humidity and energy consumption in a building space. The simulation bases on the EMPD method, which was performed by EnergyPlus, a simulation tool developed by DOE, to simulate the indoor moisture variation in a one-zone residential unit based on the Effective Moisture Penetration Depth Method, which is more suitable for practical building design processes.
Abstract: Prior research has not effectively investigated how the
profitability of Chinese branches affect FDIs in China [1, 2], so this
study for the first time incorporates realistic earnings information
to systematically investigate effects of innovation, imitation, and
profit factors of FDI diffusions from Taiwan to China. Our nonlinear
least square (NLS) model, which incorporates earnings factors,
forms a nonlinear ordinary differential equation (ODE) in numerical
simulation programs. The model parameters are obtained through
a genetic algorithms (GA) technique and then optimized with the
collected data for the best accuracy. Particularly, Taiwanese regulatory
FDI restrictions are also considered in our modified model to meet
the realistic conditions. To validate the model-s effectiveness, this
investigation compares the prediction accuracy of modified model
with the conventional diffusion model, which does not take account
of the profitability factors.
The results clearly demonstrate the internal influence to be positive,
as early FDI adopters- consistent praises of FDI attract potential firms
to make the same move. The former erects a behavior model for the
latter to imitate their foreign investment decision. Particularly, the
results of modified diffusion models show that the earnings from
Chinese branches are positively related to the internal influence. In
general, the imitating tendency of potential consumers is substantially
hindered by the losses in the Chinese branches, and these firms would
invest less into China. The FDI inflow extension depends on earnings
of Chinese branches, and companies will adjust their FDI strategies
based on the returns. Since this research has proved that earning is
an influential factor on FDI dynamics, our revised model explicitly
performs superior in prediction ability than conventional diffusion
model.
Abstract: In recent five decades, textured yarns of polyester fiber produced by false twist method are the most
important and mass-produced manmade fibers. There are
many parameters of cross section which affect the physical and mechanical properties of textured yarns. These parameters
are surface area, perimeter, equivalent diameter, large
diameter, small diameter, convexity, stiffness, eccentricity, and hydraulic diameter. These parameters were evaluated by
digital image processing techniques. To find trends between production criteria and evaluated parameters of cross section, three criteria of production line have been adjusted and different types of yarns were produced. These criteria are
temperature, drafting ratio, and D/Y ratio. Finally the relations between production criteria and cross section parameters were
considered. The results showed that the presented technique can recognize and measure the parameters of fiber cross section in acceptable accuracy. Also, the optimum condition
of adjustments has been estimated from results of image analysis evaluation.
Abstract: Automatic keyphrase extraction is useful in efficiently
locating specific documents in online databases. While several
techniques have been introduced over the years, improvement on
accuracy rate is minimal. This research examines attribute scores for
author-supplied keyphrases to better understand how the scores affect
the accuracy rate of automatic keyphrase extraction. Five attributes
are chosen for examination: Term Frequency, First Occurrence, Last
Occurrence, Phrase Position in Sentences, and Term Cohesion
Degree. The results show that First Occurrence is the most reliable
attribute. Term Frequency, Last Occurrence and Term Cohesion
Degree display a wide range of variation but are still usable with
suggested tweaks. Only Phrase Position in Sentences shows a totally
unpredictable pattern. The results imply that the commonly used
ranking approach which directly extracts top ranked potential phrases
from candidate keyphrase list as the keyphrases may not be reliable.
Abstract: Acoustic Imaging based sound localization using microphone
array is a challenging task in digital-signal processing.
Discrete Fourier transform (DFT) based near-field acoustical holography
(NAH) is an important acoustical technique for sound source
localization and provide an efficient solution to the ill-posed problem.
However, in practice, due to the usage of small curtailed aperture
and its consequence of significant spectral leakage, the DFT could
not reconstruct the active-region-of-sound (AROS) effectively, especially
near the edges of aperture. In this paper, we emphasize the
fundamental problems of DFT-based NAH, provide a solution to
spectral leakage effect by the extrapolation based on linear predictive
coding and 2D Tukey windowing. This approach has been tested to
localize the single and multi-point sound sources. We observe that
incorporating extrapolation technique increases the spatial resolution,
localization accuracy and reduces spectral leakage when small curtail
aperture with a lower number of sensors accounts.
Abstract: In this study, solid phase micro-extraction (SPME)
was optimized to improve the sensitivity and accuracy in
formaldehyde determination for plywood panels. Further work has
been carried out to compare the newly developed technique with
existing method which reacts formaldehyde collected in desiccators
with acetyl acetone reagent (DC-AA). In SPME, formaldehyde was
first derivatized with O-(2,3,4,5,6 pentafluorobenzyl)-hydroxylamine
hydrochloride (PFBHA) and analysis was then performed by gas
chromatography in combination with mass spectrometry (GC-MS).
SPME data subjected to various wood species gave satisfactory
results, with relative standard deviations (RSDs) obtained in the
range of 3.1-10.3%. It was also well correlated with DC values,
giving a correlation coefficient, RSQ, of 0.959. The quantitative
analysis of formaldehyde by SPME was an alternative in wood
industry with great potential
Abstract: There have been significant improvements in automatic
voice recognition technology. However, existing systems still face difficulties,
particularly when used by non-native speakers with accents.
In this paper we address a problem of identifying the English accented
speech of speakers from different backgrounds. Once an accent is
identified the speech recognition software can utilise training set from
appropriate accent and therefore improve the efficiency and accuracy
of the speech recognition system. We introduced the Q factor, which
is defined by the sum of relationships between frequencies of the
formants. Four different accents were considered and experimented
for this research. A scoring method was introduced in order to
effectively analyse accents. The proposed concept indicates that the
accent could be identified by analysing their formants.
Abstract: The paper deals with the kinematics and automated
calculation of intermittent mechanisms with radial cams. Currently,
electronic cams are increasingly applied in the drives of working link
mechanisms. Despite a huge advantage of electronic cams in their reprogrammability
or instantaneous change of displacement diagrams,
conventional cam mechanisms have an irreplaceable role in
production and handling machines. With high frequency of working
cycle periods, the dynamic load of the proper servomotor rotor
increases and efficiency of electronic cams strongly decreases.
Though conventional intermittent mechanisms with radial cams are
representatives of fixed automation, they have distinct advantages in
their high speed (high dynamics), positional accuracy and relatively
easy manufacture. We try to remove the disadvantage of firm
displacement diagram by reducing costs for simple design and
automated calculation that leads reliably to high-quality and
inexpensive manufacture.
Abstract: Due to important issues, such as deadlock, starvation,
communication, non-deterministic behavior and synchronization,
concurrent systems are very complex, sensitive, and error-prone.
Thus ensuring reliability and accuracy of these systems is very
essential. Therefore, there has been a big interest in the formal
specification of concurrent programs in recent years. Nevertheless,
some features of concurrent systems, such as dynamic process
creation, scheduling and starvation have not been specified formally
yet. Also, some other features have been specified partially and/or
have been described using a combination of several different
formalisms and methods whose integration needs too much effort. In
other words, a comprehensive and integrated specification that could
cover all aspects of concurrent systems has not been provided yet.
Thus, this paper makes two major contributions: firstly, it provides a
comprehensive formal framework to specify all well-known features
of concurrent systems. Secondly, it provides an integrated
specification of these features by using just a single formal notation,
i.e., the Z language.